Persistence, teamwork, and some healthy competition

When Veronica Calzadilla Sosa transferred to MIT from Miami Dade College in Florida, she was an incoming second-year student with an interest in chemical engineering. She didn’t know how involved she would soon become as a student leader in the department.

She would also go on to discover her competitive side.

At the encouragement of a friend who was then a team captain, Calzadilla Sosa joined MIT’s chapter of American Institute of Chemical Engineers, and the two worked with the Department of Chemical Engineering to build up the team of students representing MIT in the organization’s lively chemical engineering competitions. As the organization’s competition chair last year and the vice president of external relations this year, she has fallen in love with the club and found joy in bringing students together to work toward a common goal and have fun along the way.

When she first took on the role, MIT was new to the competition, and students were participating in only one of several events. Now, they participate in three categories: ChemE Cube (where teams build a miniature chemical plant that fits inside a 1-cubic-foot cube), ChemE Jeopardy (a “Jeopardy!”-style trivia competition), and ChemE Sports (where teams operate and optimize a virtual chemical plan). 

Calzadilla Sosa also captained MIT’s first ChemE Sports team, working alongside two first-year students. At their first competition, their challenge involved optimizing a distillation column, drawing on concepts Calzadilla Sosa was learning in her separation processes class. The team placed second at regionals.

“The competition was challenging, technical, and at times stressful, but also incredibly fun and rewarding,” she said after the event. “Experiences like this remind me how much engineering extends beyond technical knowledge alone.” 

For Calzadilla Sosa, the experience was about more than the result. It gave her the chance to take on a leadership role, work through unfamiliar problems with her teammates, and help create an opportunity for students who might not otherwise have participated.

Building community has been particularly important to Calzadilla Sosa, who began her undergraduate education in Cuba before moving to the U.S. When she later transferred to the Institute after earning her associate degree from Miami Dade, where she was part of the Honors College, “I was a sophomore for the third time,” she jokes. At that point, many of her new classmates had already spent a year getting to know one another and finding their footing.

She began to find her place in an unexpected setting: office hours.

During her first chemical engineering class at MIT, Calzadilla Sosa regularly went to office hours for help with difficult problems. She soon noticed that she was not the only one struggling.

“I was there because I was struggling with a problem, but then I would see more people also struggling with the same exact things,” she says. “And that, for some reason, gave me this idea that I wasn’t alone in that sense.”

Those shared struggles became a starting point for conversations, friendships, and a support system. She learned that finding a community did not necessarily mean having everything figured out. 

“Sometimes you find your community simply by allowing yourself to struggle alongside other people,” she says.

Throughout her undergraduate experience, Calzadilla Sosa has also explored the many ways chemical engineering can be applied beyond the classroom. 

While studying in Miami, she interned with the U.S. Food and Drug Administration, analyzing data on toxic elements in food, and with the engineering consulting firm Jacobs, where she learned about water and wastewater infrastructure projects in the county. As an MIT student, she has been a materials intern at the medical device company Convatec, and a materials chemistry/chemical engineering intern at the startup Folia Materials. 

In the process, she has gotten a closer look at different industries and begun to figure out which ones interest her most. At MIT, she has become particularly interested in energy systems and how existing resources and infrastructure can be used more efficiently.

“I think exploring different areas is very valuable,” she says. “I find myself thinking ‘Maybe I could do this or I could do that. Maybe I don’t like this. Maybe I prefer doing another thing.’”

Outside of her studies, Calzadilla Sosa enjoys cooking and baking for family and friends, traveling, and going to concerts and dance performances. She also likes bringing people together, especially when she returns to her first home in Cuba and has the chance to reconnect with loved ones.

As graduation approaches, Calzadilla Sosa is excited to leave student life behind and see where her degree takes her. She has not settled on one career path, but she is comfortable with that uncertainty. After studying at multiple institutions and exploring different corners of chemical engineering, she knows there is still plenty left to discover.

“I spent so many years as an undergrad, so I’m really excited to go to industry and take that next step and see the results of my education,” she says.

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This design software reimagines everyday objects as self-aware devices

As a child, you likely saw a few Disney movies depicting inanimate objects, such as clocks, cups, and toys, as interactive companions to humans — an act of pure magic, seemingly. But scientists at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are now doing something similar: transforming stationary items into self-aware tools that perceive and respond to human motion to complete a task.

Engineers have 3D-printed these dynamic items with built-in sensing, using conductive materials for sensors and traces (sort of like wires) inside. The issue: both components were typically fabricated using the same material, so they’d emit similar signals. It’s sort of like hearing two radio stations at the same time, a mixup that’s hard to interpret. This confuses, say, a glove that relays instructions to a robotic hand about how to handle a specific object. The device couldn’t filter out the noise or verify the angle of a user’s motions, leading a humanoid student to make errors.

Researchers at CSAIL and Tianjin University (TJU) in China may have found a way to 3D print more precise interactive items. With their “X-Hinges” software, users can customize a design, and the tool will automatically embed two different materials: a filament for the sensors designed to send the strongest signal possible, and another for the wire-like elements that don’t interfere. Interactions won’t get lost in translation, meaning users can fabricate objects that respond in real-time, such as small robots, household decor, object-detection systems, and toys.

With X-Hinges, users can put together an item by selecting and connecting different shapes, then choosing how certain parts move. The item won’t be limited to moving in just one way like previous approaches; instead, users can select up to three “axes:” compressing, up and down, or to the sides. Building a robotic hand, for example, you’d likely want its fingertips to move vertically and laterally. The new tool would then embed sensors where the object bends (in this case, its joints) to capture motion data from both angles. That way, the device can understand and respond to your interactions more dynamically once it’s 3D-printed.

“It’s kind of like adding a conscious element to everyday objects,” says Jiaji Li, MIT electrical engineering and computer science (EECS) postdoc and CSAIL researcher, who is a senior author on a paper introducing the work. “What you get is objects that better understand how they’re being used and have more ways to respond. In the same way an AI agent is programmed to make certain decisions based on our instructions, these creations have built-in sensing to adaptively react to human touch.”

Jiaji Li and lead author Xiang Chang, a TJU PhD student and visiting researcher at CSAIL, used X-Hinges to create many clever devices. For example, they made a glove that can teach a robot how to grasp blocks. It adjusts to the size of a user’s hands, then records how the joints in their fingers bend via sensors before rapidly relaying that information to a humanoid hand to mimic it. The glove could be useful in factories or homes, where a robot often needs to learn new interactions quickly.

The researchers also produced a small, origami-style lamp using X-Hinges. It senses when a human pinches it closed and adjusts its brightness accordingly. When you turn on this adaptive, portable light source (sort of like a reading light), it looks like a piece of folded-up paper that sprouts into a lamp.

X-Hinges can even assemble devices that identify which objects have been placed on it. You could put a banana on top, for instance, and it’ll recognize the fruit almost immediately based on the tactile data it’s recorded using its sensors. This advanced physical awareness could be integrated into detection systems in places such as airports and grocery stores. 

Behind each of the scientists’ creations is an easy-to-use interface that helps you design interactive objects from scratch. Users can choose how each part of their design looks and moves, just as the researchers did when making a video game controller that resembles a cartoon shark.

X-Hinges gives you four shapes to choose from: a custom option, cylinder, rectangle, and thin outline. To recreate the unique look of a shark’s tail, the researchers designed their own shape. They then chose how the toy bent, opting for its tail to move up and down, sort of like a joystick. Finally, the program embedded the sensors, and the scientists 3D-printed their device.

The researchers say that X-Hinges’ diverse motions are a novel feature compared to past attempts to 3D-print responsive everyday objects. “Most methods only allow for one axis of motion, often due to signal interference. X-Hinges enables your 3D-printed item to move from three angles,” says Chang. “Ultimately, you get a design with the intended movement you want. It also records motion data in each of those areas at the same time, making the device responsive to different kinds of interactions.”

The tool could help realize the untapped potential of the seemingly mundane. Objects we use every day for a specific purpose, like a water bottle for drinking or a lamp for lighting, could become interactive gadgets. Much like how a chatbot uses a sort of digital intelligence to answer your prompts, an object could leverage a kind of physical intelligence to execute a physical task when users interact with it.

For now, though, X-Hinges faces a calibration bottleneck. Each time an item is 3D-printed, its layout of electrical elements varies slightly, so two devices that appear identical from the outside may not make the same sensor readings. This is crucial if you’re building a deformable fitness glove, for instance, for two separate users. To fix this, Chang and Li built a computer vision system that can recalibrate outputs to align, ensuring data is accurate across two of the same items, although they hope to develop a built-in signal recalibration mechanism in the future.

That ambition traces back to the throughline in Jiaji Li’s own research: letting actuation and sensing “grow” directly inside a 3D-printed object, instead of adding them on afterward. He previously built printed tendon-driven mechanisms that gave objects the ability to move; X-Hinges is how he’s now building on the ability to sense. The next step, he says, is combining the two in a single print — it’s actuation and sensing born together in the same fabrication process, opening the door to new physical platforms for embodied intelligence and AI agents.

Chang and Li wrote the paper with MIT associate professor of EECS and CSAIL principal investigator Stefanie Mueller and recent TJU graduate Haiyang Yan. Their work was supported, in part, by a postdoctoral research fellowship from Zhejiang University and the MIT-GIST Program.

The researchers will present their work at the ACM Symposium on User Interface Software and Technology in early November.

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MIT’s Kavanaugh Fellowship: From invention to impact

Entrepreneurship and MIT have become a classic pairing, with a storyline that seems to write itself: A researcher develops a brilliant innovation in the lab, spins out a company, and brings a product to market that saves lives or improves society. It happens, sure — but long-term startup success is far from guaranteed.

That’s the challenge that prompted the launch of the MIT Kavanaugh Translational Fellows Program a decade ago, giving scholars who want to turn academic research into solutions to pressing challenges the time, tools, and business training to improve their chances of success.

“MIT has this world-class research facility and faculty and everything, but it also has world-class entrepreneurial programs,” says Nick Diaco, an MIT postdoc and 2025 Kavanaugh Fellow, in a new video about the program. “You really need both if you actually want to take an idea from the lab and put it into the real world and put it into situations where it’s actually affecting people’s lives.”

The program’s focus reflects a fundamental challenge for academic innovators: developing a promising technology is only the beginning. Turning it into a viable business requires making difficult decisions about customers, markets, financing, and other factors that may fall outside a typical researcher’s expertise.

“Even in a place like MIT, the majority of those people who choose to start businesses or bring that product to another business, the majority are going to fail,” said philanthropist Bart Kavanaugh at a May event announcing the 2026 fellows. Kavanaugh is one of the namesakes of the Saks-Kavanaugh Foundation, which supports the fellowship. He and his wife, Betty Saks, run the organization.

The foundation, he explained, analyzed what distinguishes successful startups. The selection process for the fellowship, he told the three new fellows — John Zhang, Maximiliano Jara Fornerod, and Xinyuan Zhang — is intended to identify researchers who have the potential to succeed.

The three are developing technologies ranging from a faster way to manufacture custom optical lenses to at-home strep throat tests and infrared detectors that can operate without energy-intensive cryogenic cooling.

They join a growing legacy of Kavanaugh Fellows whose research has moved toward commercialization, including Sublime Systems, a manufacturer of low-carbon cement; SiTration, which develops technology for extracting materials; and Stratagen Bio, which develops tools for quantitative biomarker assessment.

The yearlong program, managed by MIT’s Department of Materials Science and Engineering, gives MIT scholars time to focus on the business side of their ideas and develop the planning and decision-making skills needed to move promising research beyond the lab.

“If while you’re doing your research, you’re able to set aside some time to investigate the commercial potential before you leave the university, you get a really good picture on, 'is this a good idea for commercialization?'” says Diana Mojahed in the video. Mojahed was a postdoc at MIT when she became a 2023 Kavanaugh Fellow and is now the CEO of Lightfinder, which makes handheld spectrometers for health care, manufacturing, and telecommunications.

“It’s so much more than just achieving good specs with whatever you’re trying to achieve. There has to be a market for it. The unit economics need to work out. There’s a lot that goes into building a company.”

Learn more about the Kavanaugh Translational Fellows Program.

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Startup plans to rejuvenate the nuclear power industry with a new manufacturing approach

Building a nuclear power plant is one of the world’s most complex construction projects. It requires thousands of trucks to ship parts, often to remote regions, where huge teams of skilled workers like electricians and welders come together to assemble everything over many years.

Financing such projects is difficult, in part, because no one wants to risk loaning money to a project that might never generate power and revenue, whether that’s due to technical failures, the inability to recruit enough talent, or regulatory hurdles.

Stated this way, it’s no surprise the average nuclear plant costs twice as much as originally expected and faces delays of many years. Those cost overruns and delays have ground the nuclear industry to a near halt: When Georgia finally turned on its Vogtle Unit 3 reactor in 2023 (seven years late), it was the first new reactor constructed in the U.S. in over 30 years.

Blue Energy wants to make deploying nuclear power plants more like wind, solar, and gas projects. The company prefabricates huge blocks of its nuclear plants at shipyards, where workers and equipment already produce huge steel structures for the oil and gas industry every day, then ships the blocks on barges to the site of the plant for final assembly.

“The nuclear problem is a construction problem,” says Blue Energy founder and CEO Jake Jurewicz ’14, SM ’15, who grew up in the construction industry and studied the differences between nuclear and oil and gas projects at MIT. “On paper, nuclear technology is almost perfect: It operates above 90 percent capacity, it’s zero carbon, dispatchable, extremely high reliability, and has predictable cash flow. We don’t have enough nuclear power because we’re really bad at building it. But there’s already a huge manufacturing supply base for offshore oil and gas and offshore wind. If we can point that toward building nuclear plants, and finance it the same way, we can reinvigorate the industry.”

Blue Energy’s prefabricated blocks weigh around 1,500 tons and are designed to be easily assembled at their destination to complete a nuclear power unit over the course of a single year. The company is further reducing barriers to financing and speeding up construction timelines by designing its early plants to run on gas initially before switching to nuclear reactors, which it hopes will generate revenue within three years from the start of construction.

The company has already gained approval from the Nuclear Regulatory Commission for its gas-to-nuclear approach and has also secured an agreement with GE Vernova Hitachi Nuclear Energy for its first project, a 2.5 gigawatt hybrid nuclear power plant in Victoria, Texas, that is scheduled to begin producing power in 2030. This September, Blue Energy submitted the first part of its application to the NRC to begin construction on its Texas project, making it just one of five companies to do so in the current nuclear development era.

“Our first site is a great power generation project for that community because it's going to generate a lot of excess power,” Jurewicz says. “It’s going to show a new model for the world: This is a way the U.S. and its allies can deliver a turnkey nuclear power plant and turnkey energy sovereignty.”

A new blueprint for nuclear

Jurewicz grew up in Chicago, where he worked as a construction draftsman through high school. When he arrived at MIT, he double majored in nuclear engineering and physics, then stayed at MIT for a masters in the Department of Nuclear Science and Engineering. He also minored in energy studies through the MIT Energy Initiative.

Jurewicz’s master’s thesis explored ways nuclear power plant construction could apply lessons from the offshore oil and gas industry.

“If you’re trying to solve the construction problem, find parallel industries where people have solved it before,” Jurewicz says. “That’s why I looked at offshore oil and gas as well as nuclear shipyards in the U.S. and South Korea. We build oil and gas plants all the time, so what looks different about the way we build and execute an oil and gas plant relative to how we build a nuclear plant? They’re both mostly steel welding.”

Shipyards have several advantages over other sites for building nuclear power plants. For one, they already have thousands of skilled workers and loads of specialized equipment. They can also manufacture things in controlled environments, enabling increased automation and reducing uncertainty.

Following graduation, Jurewicz worked in corporate strategy at the utility company Exelon Energy, where he sponsored research at MIT. He originally considered starting Blue Energy as a graduate student with an approach that included creating a new passive safety system and going through a new regulatory insurance framework.

When he founded Blue Energy in 2023, he wanted to minimize risks with a more conventional reactor design. That includes prefabricating functional chunks of the reactor — what the company calls “Blue Blocks” — at a shipyard using standard manufacturing approaches that meet nuclear licensing and quality assurance requirements.

“The 1,500-ton Blue Block prefabricated modules are fully functional mechanically and electrically, they have plumbing — everything is delivered ready to run directly to the site,” Jurewicz says. “Then we have this gas-to-nuclear technology that allows us to get things going earlier with gas by building the whole nuclear steam turbine system right away and energizing it with steam from gas combustion turbines, which means we can finance it as a gas plant, so the cost of capital goes down. It dramatically lowers the cost of the project, and it reduces risk. Then we switch it with the nuclear reactor.”

Blue Energy’s nuclear reactor will be a small modular light water reactor that has already been approved by the Nuclear Regulatory Commission and is made by GE Vernova Hitachi Nuclear Energy.

Blue Energy’s first power plant in Texas will provide 1 gigawatt of power using two GE Vernova gas turbines in 2030 and then add another 1.5 gigawatts of power from up to five small modular reactors beginning in 2032.

“It will be pretty easy to add more modular reactors to the site, so we can lower the cost to that community to provide things like water desalination, which is a big issue in south Texas,” Jurewicz says. “This power infrastructure is clean, reliable, and resilient through hurricanes or any other weather scenario that can happen in that community. It creates hundreds of high-paying permanent jobs and the foundation for a lot of local economic growth.”

Faster, cheaper nuclear

Historically, nuclear power plants have taken 10-plus years of construction. Blue Energy believes it can shorten that to about 36 months. The company is projecting power from later projects to reach about $5,000 per kilowatt. For context, the Vogtle nuclear plant delivers power at more than twice that cost.

Jurewicz believes Blue Energy’s lower prices could finally inject much-needed life into the U.S. nuclear industry.

“Despite all of the excitement around nuclear, you haven’t seen real power purchase agreements get signed because there’s a stalemate on who’s going to take the construction overrun risk,” Jurewicz says. “The government doesn’t want to take it. The construction companies don’t have the balance sheet to take it. The utilities can’t take it. Even the hyperscalers won’t take a two-or-three-times cost overrun risk. Blue Energy is introducing a fifth party to break the stalemate, which is the shipyards and fab yards, which are best positioned to take the risk because they can make things in a controlled fabrication environment, so they'll take the risk on construction in their own yards.”

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For students with their sights set on space medicine, a new community takes flight

Since its launch two years ago, MIT’s Doctors Without Gravity club has already amassed more than 100 student members. The club was co-founded by graduate students Anna Wadhwa and Nicole McGaa, who now serve as president and vice president, respectively.

Bringing together students from MIT and Harvard University who are interested in the intersection of medicine, health, and space exploration, Doctors Without Gravity is the student chapter of the Aerospace Medical Association (AsMA) and the Aerospace Medical Student and Resident Organization (AMSRO). The club is open to both undergraduate and graduate students from both institutions.

Students interested in the club do not need to be aero/astro, biology, or pre-med majors, says Wadhwa, noting that the club also has many mechanical engineering students interested in spacecraft mechanics, for example. Wadhwa adds that all majors are welcome to join.

“We want to help increase student awareness and education about aerospace medicine as a potential field that people can study and pursue for a career,” says Wadhwa, who is part of the Aerospace Physiology Lab and pursuing a PhD in aeronautics and astronautics at MIT before returning to Harvard Medical School to complete her medical degree. “We hope to achieve this by connecting the existing communities that are already in place at Harvard, MIT, and Boston by hosting events, lightning talks, and our annual symposium.”

Building a community around space medicine

To bring community members together, Doctors Without Gravity hosts general social events where members can get to know one another and network in a casual setting. They also hold workshops and fireside chats with faculty, researchers, physicians from Massachusetts General Hospital, and residents in training, so students can ask questions, learn more about their research, and ask for career advice. “It’s a great way to get students plugged into the Boston area network of people interested in space medicine,” says Wadhwa.

The club’s director of science communications, Maryam Hiradfar, a graduate student in the Harvard Biophysics Program, says the club’s interdisciplinary membership is one of its greatest strengths.

“Members are a diverse group of students who can all learn from one another. We have members who are not doing active space research or space life research, including myself, but I think just being able to spark that interest in them and hopefully give people direction to get involved in that kind of research if they're interested.”

She adds, “members of the club pursue a wide variety of fields after graduating, including medical consultants, physicians, and research. Some people go into academia and research. There are numerous ways to explore space medicine; it doesn't have to be just as a flight surgeon at NASA. People interested in the field also work at Mission Control to monitor astronauts' health not only while in space, but also on a daily basis, while others do contract work for SpaceX or Axiom Space.”

The club also helps students learn about career opportunities as they arise. Wadhwa notes that if SpaceX, NASA, Axiom Space, Blue Origin, or other groups reach out to the club with job or internship possibilities, the information is quickly passed along to its members.

Faculty advisor and director of the Aerospace Physiology Lab, Associate Professor Lonnie Petersen, adds, “Doctors Without Gravity brings together curious students from many different fields who share an interest in advancing medical care beyond Earth. As faculty advisor, I am proud to support these students, expand their network, and provide opportunities for them.”

Researching the effects of spaceflight on the human body

Hiradfar is conducting research in the Integrated Positron Emission Tomography and MRI lab at the Martinos Center for Biomedical Imaging. Much of her time is spent scanning patients on a total-body positron emission tomography system. She does everything from scanning to adapting and developing conventional analysis pipelines and algorithms to analyze this new type of whole-body scan.

Wadhwa is conducting research in the Aerospace Physiology Lab with Petersen. Her work specifically focuses on how the brain reacts to spaceflight, because astronauts experience fluid shifts while in space and it is crucial to understand how those changes affect brain health. She is studying this both on a cellular and a systems level.

Both Wadhwa and Hiradfar say they would like to take flying lessons one day, but their schedules are too busy at the moment.

Helping colleagues with a study, Wadhwa did have the opportunity to take a ride in a centrifuge, accelerating from 1G to 4G — the equivalent of 88 mph.

“The test was designed to simulate the dynamics of flight maneuvers of a jet, in order to study patient physiology. It would go up for five seconds and then back down and then up and down. At the end, you do feel like you just got off a roller coaster, and I had to stay really still for a few minutes after the centrifuge finished,” she says.

Upcoming events

Doctors Without Gravity is already planning for their 2027 Symposium to be held during Massachusetts Space Week, April 19-25, 2027. Additional details will be announced as they become available.

At last year’s annual symposium, the keynote speaker was MIT Professor Dava Newman, Apollo Program Professor and director of the Human Systems Lab, who brought some samples of flight testing materials for everyone to see and touch. In 2025, the keynote was given by Erik Antonsen, director of the Mass General Brigham Space Medicine Fellowship. 

For students interested in exploring the possibilities of aerospace medicine, Doctors Without Gravity offers a place to learn, make connections, and discover the many paths into the field. Students interested in potentially joining the club may join the group’s mailing list.

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Tod Machover’s new symphony plays with AI while reflecting on democracy

Innovation, reflection, and celebration will blend at the Boston Symphony Orchestra this week, where MIT composer Tod Machover’s inventive new work “already and not yet” will see its world premiere on Thursday.

Machover, one of the world’s most prominent composers, has incorporated multiple ongoing interests into the new symphony, including AI tools interacting with the musicians, and a piece that is structured as a meditation on the crisis and promise of democracy. 

“An orchestra is an interesting ensemble to use for thinking about how different groups of people can relate to each other,” says Machover, who is the Muriel R. Cooper Professor of Music and Media and faculty director at the MIT Media Lab, where he also serves as director of the Opera of the Future group. 

He adds: “John Cage used to say one way to think of a piece of music is that it should be like the society you’d like to live in. I was always inspired by this idea, and thought of the orchestra — and constructed this new piece — in this way.” 

If the innovation in “already and not yet” comes from its use of artificial intelligence, and the reflection pertains to democracy, the celebration involved in the event partly relates to MIT: The performances are coordinated with the MIT Media Lab’s 40th anniversary celebrations occurring this week. Machover has been a member of the Media Lab since it opened. 

“In many ways, the piece is also an homage to the lab and to its spirit of invention and reinvention,” Machover says. 

The acclaimed conductor Kent Nagano — a longtime collaborator and advocate for Machover’s music — will lead the Boston Symphony Orchestra’s performances, which are taking place Oct. 22-24 at Boston’s Symphony Hall. 

Inspired by the possibilities

Machover’s extensive career has often featured the invention of new technologies within his compositions. Among many other technologically related projects, he has led the development of hyperinstruments, which can be responsive to the playing techniques of musicians and expand their range of expression; renowned cellist Yo-Yo Ma is among those who have performed Machover’s work using them. 

Working across diverse musical forms, Machover’s 2010 opera “Death and the Powers” was a Pulitzer Prize finalist. He has also used locally sourced and community-created sounds as additional aural layers in his “City Symphonies,” which have been created around the world. The next project in the series, underway in Seoul, South Korea, is scheduled for premiere in September 2027.

“I’ve always been inspired by the possibilities of technology and the expressive potential it opens up,” Machover says. “It is kind of the core language of our time and something we have to grapple with so that it evolves in the most positive human-enhancing ways. I feel so fortunate that I have been able to pursue this vision at MIT, and particularly at the Media Lab, for all these years.” 

Machover’s “already and not yet” reflects on democracy in multiple ways. One is through the form of the composition, which has three movements relating to different stages of democracy. In the first movement, “Smash Up,” strings and winds eventually get crowded out by what Machover calls the “oppressive, aggressive” sounds of brass, percussion, and electronics. The second movement, “Wake Up,” presents a moment to reflect and regroup, but little by little weaves together a thriving melodic and textural presence. The third movement, “Stand Up,” involves more vigorous interplay between all the musicians, inviting the players to participate in establishing a new kind of balance between individuality and community. 

In this way, “already and not yet” conceptualizes the orchestra as a way of representing the stress and revival of democracy, and uses a “Live AI” system created at the Media Lab — along with layers of electronics crafted in Machover’s studio — to emphasize this struggle and progression. In the second movement of “already and not yet,” the AI tools aim to underscore the distinctiveness of each instrumentalist, establishing an ensemble of soloists; in the third movement, more broadly representing the regrowth of a polity, the AI system aims to find common ground, building new sonic bridges across the orchestra and extending it out into the hall using extra, specially installed loudspeakers. 

“I’ve used the way the orchestra plays, how much is scripted and how much freedom they have, and how they negotiate their relationship with the conductor, as part of the story,” Machover says. “It’s not said explicitly, but I think the players and the audience will feel it. It’s a whole society up there on stage, and the liveliness and ever-changing nature of the AI systems for this piece both dramatize and encourage a new way of playing and listening.”

Machover credits two PhD candidates in his group at the Media Lab for their extensive work on the project: Manaswi Mishra, who designed and built the AI systems for the performances, and Ana Schon, who will be doing the complex sound mixing in Symphony Hall during each performance. 

Reflections of an AI veteran

For Machover, the application of machine learning and AI is hardly a newfound idea; he has been exploring the concept for decades, giving him a distinctive perspective on this topic du jour. 

“The current generation of AI, especially generative AI, has capabilities that are different than AI from 20 or 30 years ago,” Machover says. “It’s good at certain things that were hard to do 20 years ago, but less good at some things that were easier to do back then.” 

When he designed a hypercello for Yo-Yo Ma, for instance, those systems would analyze Ma’s sound, playing techniques, and expressive intent in order to shape the extensions of the instrument. Today’s AI tools “are less good at analysis, but very good at detecting significant features and patterns in the audio itself, information that can be leveraged to powerful musical effect,” Machover says. 

“Current systems aren’t so good at what we did [for Yo-Yo Ma], like trying to understand the performance or the music itself,” Machover says. “But evolving AI models do an incredible job — especially in Manaswi’s magical systems — at establishing an immediate, creative dialogue with musicians, producing sophisticated and surprising augmentations that in turn inspire performers or composers to discover truly new ideas.”  

Ultimately, Machover says, “I think this piece — through its technology, its ‘story,’ and its sounds — is meant to take people on a journey of recognition about where we are at this moment in time and where we might be going. It’s meant to be an optimistic and inspiring piece.” He adds, “The idea, expressed in the work’s title, is that we’re so lucky to be at this place in this moment, even with everything that’s wrong and in critical need of repair. We really are. At the same time, it’s so urgent to realize that the vision of a just and flourishing society, for which the foundation exist, isn’t finished at all. Not only that, it’s in crisis. So this is the last time to be complacent, or discouraged.”

For all of that, Machover also expresses hope that the audience at Symphony Hall can simply engross themselves in the music itself, and find it compelling on its own terms. 

“My biggest wish is that people listen to this piece as music — forget about the AI or the story and just get swept along,” Machover says. “There’s one melody in this piece that’s trying to express itself in the first movement, and appears in fragmented form in the second movement. In the third movement, it’s the center of everything, a kind of vision of resolve, hope, and purpose. If people come out of the performance and don’t have some part of that melody in their heads, I’d be surprised. I hope that audiences listen for that, try to hold on to it, and see where it might lead.”

The piece was commissioned by the Boston Symphony Orchestra and supported by the New Works Fund of the Massachusetts Cultural Council.

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MIT student team CERBERUZ wins NASA LunaRecycle Centennial Challenge, turning lunar trash into tools

Establishing a human presence on the moon will require state-of-the-art spacecraft, spacesuits, life-support systems, and some of the most sophisticated technology humans have ever built. It will also require figuring out where to put the garbage.

A future lunar outpost will receive a steady stream of supplies from Earth, bringing packaging and other materials that could quickly become a mountain of waste. Meanwhile, astronauts will need tools, replacement parts, and materials to maintain the outpost, and shipping supplies from Earth is astronomically expensive. An MIT student team has won first prize in a NASA competition for developing a way to turn that trash into useful materials for lunar living.

The Composites for Extraterrestrial Recycling By Engineering the Reuse and Upcycling of Zotek (CERBERUZ) team was named first-prize winner in both the Prototype and Digital Twin tracks of NASA’s LunaRecycle Challenge. The challenge — part of NASA’s Centennial Challenges series — asked participants to design and develop solutions that can reuse, recycle, or upcycle space waste and improve the sustainability of longer-duration lunar missions. Teams were encouraged to envision solutions that not only addressed recycling in deep space, but could also have applications on Earth.

The CERBERUZ team’s system turns otherwise unusable waste into new composite materials, grinding it down, melting it, and molding it into useful parts. The approach reduces the need for costly shipments from Earth and keeps bulky packaging from piling up in lunar landfills.

“Waste packaging materials will inevitably accumulate when a lunar outpost is built, and at the same time, outpost construction and maintenance will require a steady supply of new materials, including replacement parts,” says George Lordos, a research scientist in the MIT Department of Aeronautics and Astronautics and System Design and Management, and the lead advisor for the CERBERUZ team. “Recycling waste materials into such parts can help reduce materials needed to be launched from Earth.”

Waste not, want not

CERBERUZ separates non-biological waste into two streams: thermoplastics and everything else. All materials are then ground into a fine powder and mixed together. The powder mixture is loaded into an injection molding machine, where the thermoplastics melt with the remaining materials suspended in the molten plastic. The mixture is finally injected into a mold, producing high-quality composite parts that can be quickly and reliably replicated.
 

The team’s approach is especially notable for its treatment of Zotek F30, a closed-cell thermoset foam commonly used in aerospace packaging. Mixed thermoplastics and thermoset foams like Zotek F30 have no established recycling solutions, even on Earth. CERBERUZ takes a unique approach to this challenge by incorporating the Zotek as a reinforcing filler for the molten feedstock.

Zotek presents another peculiar engineering challenge that makes the need to break it down even more pressing: It is so lightweight that enormous quantities are needed to produce a useful mass of material. “We had big shipments of Zotek coming in, and one person can carry them on their head like it’s nothing,” says José Soto, a graduate student in AeroAstro and the team's pre-processing lead. “The box is the size of a person.”

The team designed the process around the constraints of operating far from Earth. Because CERBERUZ uses mechanical methods powered by electricity, it doesn’t rely on water-intensive recycling processes or chemical depolymerization, and produces no secondary chemical waste. This could allow packaging and other materials delivered to a lunar outpost to become a local source of manufacturing feedstock, giving astronauts the ability to produce needed items from material they already have on hand. 

“We set out to build something that would actually make sense on the moon, not just in a lab,” says Lanie McKinney, a graduate student in AeroAstro and team lead for CERBERUZ. “That means no water and no chemicals you can’t replace. Every design choice we made was driven by those constraints. And we don’t want to recycle just for recycling’s sake; we want to make useful things. Part of how we framed the problem was to create a system that can process nearly any feedstock and turn it into a wide array of components, giving more utility than producing a single item.”

Alongside the physical recycling system, the team developed DEIMOS, or Digital Environment for Intelligent Modeling of Operational Systems, a digital twin of its injection molding machine. Using data collected during actual production runs, DEIMOS models how different combinations of recycled materials and part geometries will behave during manufacturing, predicting factors including mold fill, warpage, and shrinkage risk. Ultimately, the digital twin could help astronauts determine how recycled materials will perform before committing limited resources to manufacturing a part on the moon.

Where ideas become hardware

The CERBERUZ team grew out of the MIT Space Resources Workshop, a co-curricular initiative of students passionate about designing, building, and testing systems to support future moon and Mars exploration. Founded in 2017, the workshop is well-known for building teams that take on, and conquer, grand challenges in NASA-sponsored competitions.

The team brings together undergraduate and graduate students from four MIT departments: Aeronautics and Astronautics, Mechanical Engineering, Electrical Engineering and Computer Science, and Materials Science and Engineering. Professor Jeffrey Hoffman, a former NASA astronaut, and Lordos served as advisors for the team. 

“What impresses me most about this team is the quality of leadership,” says Lordos. “Lanie McKinney has been an outstanding team lead, and the co-leads — Palak Patel on manufacturing and materials characterization, Lilly Etzenbach on the digital twin, and José Soto on pre-processing — have each built and managed subteams doing cutting-edge research in lunar sustainability.”

The win caps nearly two years of work on the challenge. CERBERUZ was selected as a Phase 1 winner in 2025 before advancing through Phase 2 and earning milestone prizes in both tracks on its way to the final demonstration in summer 2026. The team earned $925,000 in prize money over the course of the challenge, and hopes to reinvest their winnings in the Space Resources Workshop, funding equipment and facilities that will enable future teams to rise to ever-more-complex challenges. Those advances will help turn a return to the moon into something more permanent: a human presence, built to last.

“If we’re able to reduce the amount of waste that’s inevitably going to be left on the moon, rather than letting it pile up like a landfill,” Soto says, “we can preserve both the beauty of the moon and make exploration more efficient and sustainable. And perhaps we can inspire people back on Earth to take another look at our trash and find more ways to recycle or reuse it.”

CERBERUZ team leads are Lanie McKinney, Palak B. Patel, Lilly Etzenbach, and José Soto. Team members include Sophia Augier, Sophie Berkvist, Ariella Blackman, Keira Boone, Constantine Bulavenko, Seth Burrowes, Andrew Chen, Alex Chen, Chris Choe, Johnson Cristales, Brady Cruse, Hillel Dei, Natalie Hatzigeorgiu, Intia Ibnah, Avishai Jeselsohn, Mollie Johnson, Uma Kirk, Christopher Kwon, Jessica Meza, Juan Orrego, Giuliana Pertuz, Jordan Prawira, Brandy Romine, Dustin Wang, Madison Wood, and Adrian Yang. 

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Beaver Works Summer Institute: A leader in transformational STEM education

Eleven years ago, MIT Lincoln Laboratory staff member Robert Shin was challenged by a colleague to find a way to extend the resources of Beaver Works — a joint education and research center created by the MIT School of Engineering and the laboratory — to some of the best and brightest engineering students around the country. A year later, in summer 2016, the MIT Beaver Works Summer Institute (BWSI) was born. 

BWSI, which celebrated its 10th anniversary this summer, is a four-week program designed to offer high school students a transformational hands-on experience while teaching them skills to fuel their future studies and careers in science, technology, engineering, and mathematics (STEM).

"As I look back at the last 10 years of BWSI, I am humbled and grateful to be a part of this amazing journey," says Shin, who has served as the founding director and then the STEM program director for BWSI since 2016. "What started as an idea has evolved into something much bigger and more impactful than we ever imagined. Each year, our students have exceeded every expectation through their curiosity, hard work, willingness to accept challenges, and perseverance." 

Originally launched with a class of 46 students from 24 high schools across the country, the BWSI program has seen steady growth each year, both in the number of students enrolled and the total number of courses offered. In the first year of the program, BWSI offered just a single course — the Rapid Autonomous Complex Environment Competing Ackermann-Steering Robots (RACECAR) course — that challenged students to program vehicles to navigate a racetrack full of obstacles. A decade later, BWSI now offers 14 courses spanning fields such as artificial intelligence, data science, cybersecurity, quantum computing, and microelectronics to more than 440 students. 

"The nation needs innovators, problem-solvers, and leaders to tackle the national security challenges of tomorrow in a rapidly evolving world," says Melissa Choi, director of Lincoln Laboratory. "By bridging the gap between classroom theory and practical application, BWSI inspires the next generation of scientists and engineers and exemplifies the laboratory’s commitment as a federally funded research and development center to help develop the future STEM workforce." 

Beaver Works Operational Manager Lisa Kelley has been with the program from the start, for both the founding of Beaver Works in 2010 and the launch of BWSI in 2016. She recalls welcoming the first class of 46 students, adding that she never could have imagined the impact that BWSI would have a decade later. 

"Today, I look at the thousands of students who have come through our programs with immense pride and gratitude," says Kelley. "What makes me most proud is that we built something both exceptional and accessible, a program that challenges students at the highest level while expanding opportunity." 

Beyond the summer curriculum, BWSI has expanded throughout the years by offering eight-week outreach programs in the spring and fall that build technical foundations for high school students in grades 9–11 prior to entering the competitive summer program. One of these fall programs is "Girls Who Can," which focuses on engaging young girls with STEM. Additionally, in 2022 and 2023, BWSI launched national challenges that adapted the content of two of their courses (Build a CubeSat and Designing for Assistive Technology) into an eight-month team-based format with mentors. 

The BWSI curriculum has inspired collaborators to create similar programs in countries such as Greece, Japan, Canada, Mexico, Italy, and Spain, as well as parallel programs in schools and universities across the country. 

Beaver Works Manager Joel Grimm says that the growth of the program has continued to challenge and inspire him from year to year. "To me, Beaver Works and BWSI mean embracing change — saying 'yes' to something new and innovative," Grimm says. "I encourage students to step out of their comfort zone and see what’s possible, and I hope that more students understand that BWSI is a unique opportunity to take a risk and stretch beyond their expectations." 

After participating in BWSI, many students continue to engage with the program. One example is Diptanshu Sikdar, who participated in BWSI for two summers as a high school student before returning as a teaching assistant for the Quantum Software and Software Development courses. 

"BWSI transformed my curiosity about quantum computing into a strong foundation and introduced me to the beauty of algorithm design and computer science," says Sikdar, who went on to pursue a PhD in quantum science and credits his experience with BWSI for building connections that led to his current job at MITRE. "It was much more than a summer program for me; it was the point of origin for my quantum journey and the foundation for my growth as a student, researcher, teacher, and leader." 

It’s this type of transformational experience that Shin hopes BWSI students will continue to have well into the future. 

"I believe the last 10 years of BWSI were just the beginning," Shin says. "The BWSI program at MIT will continue to be impactful, and we see a future where all students interested in programs like BWSI will have an opportunity to participate and learn. Wouldn’t that be wonderful? It is not only possible, but we owe that to our next generation." 

To learn more about BWSI and how to support its mission, visit the BWSI website or email the administrator.

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MIT spinout makes surgical stitching more like applying a sticky note

Dozens of surgical procedures require doctors to connect two pieces of tissue together in a delicate stitching process. It happens in triple heart bypass, C-sections, and surgeries to repair hernias and tendons. Today, those procedures are mostly done by surgeon-controlled robots or by hand, and the margin for error is small. Even small errors in suturing or stapling can lead to leaks with devastating consequences to patients.

SanaHeal wants to make connecting tissues more like using tape. The company has developed a bioadhesive technology that can rapidly stick to wet and uneven surfaces and form air- and fluid-tight seals to simplify surgical procedures. The company’s product, first developed at MIT, was inspired by sticky materials in nature like barnacles and spider webs.

SanaHeal’s technology has already gained regulatory approval to stop trauma bleeding, and next year it will enter human trials to help control bleeding during surgeries and for repair of various injured tissues.

The startup, which collaborates with larger companies for clinical trials and commercialization, believes those applications only scratch the surface of the technology’s potential.

“If someone is struggling to put something on biologic tissues, we can help,” SanaHeal founder and chief technology officer Hyunwoo Yuk SM ’16, PhD ’21 says. “The current way of doing this is by suturing through tissues, which is painful and difficult to do perfectly during surgery. Our solution is more like a Post-it note. It’s much less invasive and easier to use with surgical robots. Also, faster and more efficient surgical procedures have potential to help lower ever-increasing costs of surgeries that are significantly straining the health care system.”

A sticking problem

Yuk conducted his master’s and PhD in the lab of Xuanhe Zhao, MIT’s Uncas (1923) and Helen Whitaker Professor of Mechanical Engineering. Initially, his research focused on the mechanical properties of soft materials called hydrogels, but about halfway through the program, he pivoted to study their biomedical applications, in part motivated by a serious accident his family member was involved in.

“We were looking at how to make these hydrogels better adhesives, and because we are in Boston, we started working with doctors and medical schools in the surrounding area,” Yuk recalls.

Those conversations made him realize how often surgeons have to seal or attach tissues. That process usually involves staples or sutures, which can cause more damage to tissues, trigger immune responses, and lead to scar tissue or infections.

“These are often tiny tissues that sometimes require needles thinner than a human hair to be used during microsurgery,” Yuk explains. “They are very difficult surgeries, and they can lead to all kinds of complications.”

Yuk realized his hydrogels offered a better solution. The materials, which are made from polymers and water, are biocompatible, meaning they minimize immune responses and scar tissue buildup. Early versions of the technology acted like double-sided tape, absorbing water from wet tissues using polyacrylic acid — an absorbent material used in diapers — to adhere to them in a matter of seconds.

Yuk had planned to stay in academia after his PhD, but as he learned more about what it would take for the technology to reach patients, he decided to focus on leading that work.

“It’s very difficult for innovations to make it into the clinic and help patients if you’re in an academic research lab,” Yuk says. “We didn’t know anything about startups, so we used resources like MIT’s Deshpande Center, the Venture Mentoring Service, and MIT’s Technology Licensing Office in hope that there might be external interest in our technology. We quickly learned the regulatory hurdles presented too much risk at the early stages for potential partners, so we had to commercialize it ourselves.”

The founders received funding from the Deshpande Center to start developing the company. SanaHeal was officially formed in 2021.

Yuk and his collaborators initially focused on applying their technology to wounds to stop bleeding. But they soon shifted to focus on surgical applications, which are more numerous.

“It’s a major unmet need,” Yuk says. “We are giving surgeons more options for a host of complex procedures. They are really excited about this.”

Partnering for impact

SanaHeal provides its technology to larger medical device company partners, who are developing products for a wide range of applications including in open, laparoscopic, and endoscopic surgeries as well as in combination with existing devices for sutureless implantation in applications like hernia and nerve repairs.

“We have envisioned ourselves as a platform company from the beginning,” Yuk says. “We don’t have the resources to develop 10 products at once, so we partner with bigger companies to commercialize solutions.”

Yuk, who has been working on the technology for nearly a decade, admits the commercialization process has taken longer than he expected. But he believes the payoff — seeing a technology he first developed in a lab have an impact on patients — will make the journey worth it.

“My life goal as a researcher is to see the full lifecycle of a new technology, from the scientific discovery, to research, to understanding how it works, to engineering it, to working with subject matter experts, and finally developing a product that gets approved to help humans,” Yuk explains. “It’s rare, but it would be incredibly rewarding and would be a great story to tell to inspire my research colleagues.”

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Symposium highlights MIT’s wide range of innovations for aging brain health

From its beginning in 2015, the premise of MIT’s Aging Brain Initiative (ABI) has been that neurodegenerative diseases such as Alzheimer’s are complex, “system-wide” breakdowns that will require advances of many kinds from many sources to address. The six talks at the ABI’s symposium “Innovations for the Aging Brain” on Sept. 25 illustrated what that’s come to mean at MIT, as scientists and engineers described their latest work to improve health for the aging brain.

“The ABI is unique because it brings together researchers from a diverse array of fields,” said ABI Director Li-Huei Tsai, Picower Professor in the the Picower Institute for Learning and Memory and Department of Brain and Cognitive Sciences (BCS). “Today’s symposium showcases MIT’s collective brilliance across neuroscience, engineering, chemistry, and beyond.”

One of the talks, for instance, featured a team effort including Giovanni Traverso, the Karl Van Tassel (1925) Professor of Mechanical Engineering and a physician at Brigham and Women’s Hospital, who has joined forces with Tsai and other collaborators to develop an artificial intelligence system that could improve personalized Alzheimer’s care by matching patients to the best prevention interventions for them. The system integrates data from clinical trials, patient lifestyle histories, and multi-omics data (e.g., genomics, proteomics) to predict an individual’s Alzheimer’s progression and likely response to interventions. 

Speaking alongside project leads Arvid Gollwitzer, an engineer-scientist in the Broad Institute of MIT and Harvard, and MIT-Novo Nordisk AI Fellow Adrián Noriega de la Colina, Traverso described how the team engineered an AI model, called FINGERS-7B, to integrate these multiple highly diverse data sources into its training, thereby amassing 8 trillion “tokens” to inform its predictions.

“Every individual is very unique in their biology, and that links to how we respond to those interventions,” said Noriega. Not only could AI predictions help tailor individual prevention measures, he added, but also it could inform clinical trial designs by better pinpointing the most appropriate populations to target with a prospective drug or other treatment.

Picower Professor Earl K. Miller focused on prevention of a different problem for the aging brain: cognitive side effects from exposure to too much general anesthesia. Noting high rates of postoperative delirium in older adults after major surgery, Miller described his research with ABI founding member and Institute Professor Emery N. Brown, a Picower Institute and BCS colleague, to develop a closed-loop system that uses brain wave-based measurements of unconsciousness to optimize anesthesia dosing. Miller and Brown’s labs have shown that regardless of their molecular means of action, multiple anesthesia drugs induce unconsciousness in the same way: by shifting brainwaves out of phase with each other, disrupting the coordination of communication across the brain’s cortex that sustains cognition and consciousness. Informed by such brain wave “signatures” of unconsciousness, the system could help anesthesiologists to safely tailor dosing during surgery.

In her talk, associate professor of mechanical engineering Ritu Raman, the Eugene Bell Career Development Chair of Tissue Engineering, described how she’s approaching the study of neuromuscular diseases, including amyotrophic lateral sclerosis (ALS) and muscular dytrophies, by developing advanced lab models of muscle tissue that also integrate nerves and vasculature. For instance, for ALS, her lab has been able to make the cultures from induced pluripotent stem cells derived from patients. The lab models give her team an opportunity to examine neuromuscular junctions in detail and to model how they change in response to potentially therapeutic drugs.

In many neurodegenerative diseases associated with aging, such as Alzheimer’s and Parkinson’s, a major pathology is misfolding and aggregation of intrinsically disordered proteins, such as amyloid-beta or alpha-synuclein. In her talk, William R (1964) and Daniel L. (1995) Young Career Development Assistant Professor of Chemistry Oleta Johnson described her lab’s work to prevent aggregation before it starts. In pursuit of that strategy, she said her lab’s research is focused on developing the chemical knowledge and means to identify proteins at issue, detect that they are moving into a problematic state, and then control their conformation.

Eugene McDermott Professor in the Brain Sciences and Human Behavior Alan Jasanoff, a member of the BCS and Biological Engineering departments as well as the McGovern Institute for Brain Research, described a very different application of chemistry to aging brain research. He described how his lab develops novel chemical probes to make molecules in the brain visible in magnetic resonance imaging. These include the neuromodulatory enzyme cholinesterase, which is the target of many of the few drugs approved to treat Alzheimer’s, and also lipids, which several brain cell types mishandle in Alzheimer’s, Tsai and others have shown. His lab has also developed technology to genetically encode a novel probe in brain cells to improve MRI visualization of brain activity.

And while many researchers focus on the prominent problems that proteins or lipids present in neurodegenerative disease, Novartis Professor of Chemistry Laura Kiessling discussed a less-appreciated but still important component of cellular function: sugars called glycans that line the surface of cells. In particular, researchers have linked a glycan called heparan sulfate to Alzheimer’s disease. Kiessling’s lab, working with ABI founding member Ed Boyden, Y. Eva Tan Professor of Neurotechnology, is working to characterize and understand glycans. Her lab, for instance, has shown that glycans of different sequences organize on cell membranes so that they can bind and recruit specific proteins to distinct regions on cells.

“We are really excited about the fact that we’ve observed this now for the first time and have a toolkit to study other diseases,” she said. Understanding glycan binding could even give scientists a means to target different cells and cellular processes.

Following the six talks, more than a dozen trainees at a poster session presented even more aging brain-related projects from around the Institute, further highlighting MIT’s diversity of research in the area, something the ABI exists to encourage.

From massive AI datasets to the sugars on individual cells, the symposium highlighted how MIT scientists are pushing the frontiers of science and engineering to improve understanding of, and interventions for, the health of the aging brain.

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Why teaching AI about symmetry could make prenatal diagnosis more reliable

Despite millions of years of evolution, the development of the human fetus remains a complex process that is vulnerable to genetic, environmental, and metabolic disruptions. These disruptions could result in developmental abnormalities, starting with one of the first organs to begin developing in the fetus that continues to develop after birth: the brain.

In a routine prenatal ultrasound, the sonographer will flag possible brain abnormalities for additional magnetic resonance imaging (MRI). But imperfect imaging can result in missed or incorrect diagnoses. 

To assist with the early detection and treatment of these abnormalities, researchers at MIT, Boston Children’s Hospital, and Inria have developed and trained a deep learning model called E(3)-Pose that helps image the fetus’s head while it’s in motion to capture a high-resolution image that the radiologist can examine. A paper about the work was presented at the 2026 European Conference on Computer Vision. 

“One of the problems with having the baby move is that the slices are all over the place,” says first author Ramya Muthukrishnan. Muthukrishnan is an MIT PhD student in the lab of Sunlin (1966) and Priscilla Chou Professor of Electrical Engineering and Computer Science Polina Golland, who is a principal investigator at the MIT Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic) and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).

By slices, Muthukrishnan is referring to a series of 2D images taken during a fetal MRI scan. These 2D planes stacked together effectively make up one high-resolution, 3D image of the fetus’s head. But if the head shifts during imaging, each 2D image “slice” could end up being taken from a different angle, resulting in gaps in the final scan and unusual slice orientation. These problems may cause the physician reviewing the MRI to miss or incorrectly diagnose a pathology in the fetal brain.

“There are very fine details that you need a very good volumetric picture of the brain to see,” explains Muthukrishnan. “If you have coverage gaps, you can’t see critical regions, and you need to be able to see well to detect abnormal development.”

What makes E(3)-Pose particularly good at tracking fetal motion is its focus on physics. Rather than simply training the model to learn physics from the data, the very principles of physics are baked into the neural network: left-right symmetry of the fetal head is embedded in the model architecture, making it easier for the model to accurately identify the brain’s orientation. 

When Muthukrishnan began working on the project at the start of her PhD, she had no background in physics, let alone MRI physics. Most of her experience was in computer science. “I was surprised when I had to go and implement this on the scanner,” she recalls. “I was not prepared for how many times I would crash the scanner because putting things on hardware and getting it to work on hardware is a different beast than training a model to run on data on a GPU.” 

Despite the challenges, Muthukrishnan persisted. She remembers shadowing a radiologist who performed fetal MRI scans at Boston Children’s Hospital at the start of her PhD and observing the shared frustration of the patient and radiologist: the pregnant mother felt uncomfortable after spending an hour in an MRI, only to quit the scan halfway; the radiologist was unable to procure a full, high-quality MRI to monitor the development of the fetus.

“Seeing frustration about it helped me decide what I wanted to do with my PhD, because it felt like this was a pain point,” Muthukrishnan says.

Fortunately, she had help: Co-author Borjan Gagoski, an assistant professor of radiology at Harvard Medical School and a researcher at Boston Children's Hospital, developed a sequence that acquires additional MRI scans to assist with training E(3)-Pose and worked with Muthukrishnan to help troubleshoot the scanner whenever it crashed. Co-author and Boston Children’s Research Assistant Aryn Lee recruited the pregnant volunteers and assisted with acquiring each of the MRI scans. Senior authors who helped guide the project include Elfar Adalsteinsson, MIT professor of electrical engineering and computer science; Ellen Grant, the Käthe Beutler Professor of Pediatrics and professor of radiology at Harvard Medical School; and Golland. Benjamin Billot, a researcher at Inria and a former postdoc in Golland’s group, helped Muthukrishnan get started with the initial method he developed.

“Ramya’s work elegantly combines geometric concepts like equivariance and symmetry with the power of deep learning to change how MRI scanners acquire the images, and to ultimately help the physicians detect and treat problems early in development. It’s an impressive research project that is deep and fundamental in how it models image acquisition, with clear clinical impact,” says Golland.

Grant, who directs the Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC) at Boston Children’s, adds that Muthukrishnan’s work “will automate fetal brain MRI, replacing today's slow, manual process with faster and more comfortable scans for mothers, while also providing higher-quality images for radiologists to interpret.”

E(3)-Pose’s applications could extend beyond motion tracking for fetal MRIs. It could assist with imaging other hard-to-image anatomy, and even autonomous driving applications, where limited sensors need to capture noisy, 3D data in order to track 3D objects.

For now, Muthukrishnan hopes to improve E(3)-Pose so that it can help with imaging second-trimester or younger fetuses, as the model is primarily trained on third trimester fetuses. Second-trimester fetuses are “so small, they move around a lot more because there’s more space in the uterus,” Muthukrishnan says. “They’re more important to focus on because the earlier you detect brain abnormalities, the easier it is to intervene.” 

This work is supported by the MIT Jameel Clinic, the MIT Takeda Program, the Chou Family Transformative Research Fund, the National Institute of Biomedical Imaging and Bioengineering, and the Eunice Kennedy Shriver National Institute of Child Health and Human Development.

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Giving AI a “crystal clear” view of the materials world

In principle, artificial intelligence could make finding the right material for an application as simple as ordering dinner: Scientists would tell a large language model what they want, and it would serve them a perfectly designed crystal for the job.

Unfortunately, that approach doesn’t work well yet, and the problem comes down to data: Most materials consist of crystals, which are 3D periodic arrangements of atoms whose structures are stored in specialized formats, not the text streams that today’s large language models are trained on. The experimental literature is also heavily biased toward a few popular classes of crystals, making AI outputs skew toward those materials.

Now MIT researchers have created a multimodal AI model that tackles these problems. The model combines 3D atomic structures with natural language descriptions to create rich linguistic descriptions about the structures from experimental research papers and first-principles computational databases. The unified description outlines not just the chemical composition and structure, but also its properties, processing considerations, and potential applications, helping AI learn more about what makes materials impactful.

In a new paper in Nature Communications, the researchers showed their system could identify better material designs than models trained on text streams alone by allowing the model to “see” the atomic arrangements and bonding patterns. For example, when the researchers asked the model to identify materials suited for solid-state lithium-ion battery electrolytes, its top results included materials that had been independently identified as promising candidates. The researchers also showed their model learned geometric representations of material structures in ways text-only models could not.

“Structure is really at the heart of the materials science field,” says Ju Li, the Carl Richard Soderberg Professor in Power Engineering in the Department of Materials Science and Engineering (DMSE). “If you understand the structure, you can infer quite a lot about the properties and performance of materials. We wanted to build the connection between a material’s atomic structure and its properties and processing for the model.”

Joining Li on a paper about the model are Yang Jeong Park, first author and former MIT postdoc; Mayank Kumaran, a recent University of Illinois Urbana-Champaign computer engineering graduate; Chia-Wei Hsu SM ’26; and Elsa Olivetti, the Jerry McAfee (1940) Professor in Engineering in DMSE.

Getting models to see in 3D

Materials scientists are always on the hunt for new crystals that will lead to the products of the future. Over the last decade, AI has reshaped that process, proposing and designing new crystalline structures, which have highly ordered atomic structures and make up more than 90 percent of solid materials on Earth. Most of those models treat solid crystalline materials as 3D graphs.

The rise of large language models has given researchers another tool for innovation. But existing large language models rely heavily on text from published papers and books, limiting their knowledge of the physical world, since many potential crystal structures are stored in computational databases. Text-based models also lack understanding of visual geometry.

To overcome those challenges, the researchers decided to create a vision-language model for crystalline materials.

They trained a language model to create textual descriptions of crystal structures using an approach known as contrastive learning, in which models compare similar and dissimilar examples of structures and textual descriptions to achieve a unified understanding. This is similar to aligning the visual and language regions of the brain.

Following training, the researchers compared the predictions of two versions of the model: one trained on a dataset containing the AI-generated descriptions and the other trained on a dataset containing text from papers only. They found that the model trained on AI-generated descriptions successfully learned how to align geometric structures with text descriptions while the other did not.

“We wanted to create an AI model that works broadly across materials,” Li says. “That’s why we decided to synthesize narratives rather than rely solely on existing papers. We found when we used that narrative dataset, the models are better at predicting the function.”

Accelerating materials science

The researchers then showed their model could be given a natural language query describing a property and identify crystalline materials with that property, outperforming a baseline.

“There are sometimes these step changes within materials science around algorithmic integration toward useful tools, which the community uses to further advance the field,” Olivetti says. “This approach helps us see more deeply into three-dimensional structures and link structures to property and processing. I hope this can be one of those step changes.”

Li compares the model to AlphaFold, an AI model that links protein structures with function that has helped advance biological research and drug development.

The researchers believe their new approach can work with many crystalline materials, and they hope other material scientists will use it to accelerate their work.

“Being able to see a three-dimensional crystal and how its atoms are connected is super foundational,” Li says. “I think this will be useful to anyone who practices materials science.”

The work was supported, in part, by the U.S. Defense Threat Reduction Agency through the University Research Alliance; the U.S. Defense Advanced Research Projects Agency; and the National Research Foundation of Korea.

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Fostering community amid Kendall Square’s innovation

Kendall Square in Cambridge, Massachusetts, is often cited as the most innovative square mile in the world. But when the Kendall Square Association gathered local stakeholders for its 18th Annual Meeting Thursday, the conversation focused on innovation primarily in the context of community.

The event, which took place at the nonprofit startup incubator The Engine, attracted people from across Cambridge, including business leaders, elected officials, local residents, and students, for a night of local food and conversation about the advance of technologies like artificial intelligence and what they mean for society.

“How can we make AI not an enemy of work, but a tool for workers to expand their capabilities and build new expertise or do new things?” asked MIT Institute Professor Daron Acemoglu in a keynote talk. “The world is at a point in time where we need new innovations and new adaptations to growing challenges.”

Acemoglu’s keynote was one of several presentations at the event, which also featured music from the Kendall Square Orchestra, a vote on new KSA board members, and awards for organizations making a positive impact through innovation.

KSA is a nonprofit made up of over 150 organizations across Kendall Square, from major companies to universities, research organizations, and the independent shops and restaurants that give Kendall Square its distinct character.

“People come to Kendall Square to make the world better,” said KSA Executive Director Beth O’Neill Maloney in her opening remarks. “People come here to improve the human condition, people come here to solve big problems, and people come here to innovate for good.”

Acemoglu, who shared the Nobel Prize in economics in 2024 for his work studying how institutions affect prosperity, spoke on the subject of his new book, “What Happened to Liberal Democracy?”

Acemoglu says liberal democracy is under siege as trust in liberal institutions decline, political polarization rises, and people lose faith in elected officials. He acknowledged that the shared prosperity liberal democracy promised has not always been delivered, especially over the last 50 years, but insisted it is the best path forward and in need of renewed support.

“I believe liberal democratic institutions, together with the norms that support them, are one of the greatest human achievements,” Acemoglu said. “It would be unthinkable for people who lived 300 years ago that we could live in societies consisting of hundreds of millions of people with diverse interests, different views, doing different things, and people still participate in politics and reach compromises, and we have state institutions that, by and large, actually provide services and do things for the people, and that we build opportunities for prosperity from which most people benefit while social freedoms are largely upheld.”

Cambridge Mayor Sumbul Siddiqui also spoke at the event. Siddiqui began her talk by telling the story of Cambridge residents working with biotech labs in the 1970s to create a groundbreaking policy on recombinant DNA research, which helped turn Kendall Square into the life science hub it is today.

“All these years later I think that story captures what makes Kendall Square so special: It’s our willingness to work together even when we face big challenges,” Siddiqui said. “It isn’t just the universities or labs, it’s also the culture of collaboration among nonprofits, governments, and residents.”

Broad Institute Chief Communications Officer Lee McGuire started his talk by reviewing a 2009 report on what made Kendall Square such a powerful driver of innovation, noting that factors like talent density, education, and a collective voice remain strong in the area today.

“This report was brilliant in that it captures so many of the special things that matter for a place like Kendall,” McGuire said. “It is the job of the Kendall Square Association and all of us to help protect those things, make sure we name them, understand them, and see them as essential elements of making sure this community stays what it is no matter what happens. As long as there’s a good idea, this is the place that’s going to get that idea moving and scale it up to change the world.”

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AI model decodes the language cells use to communicate

As an embryo develops from a small cluster of stem cells, those once “blank slate” cells begin to take on more specialized roles like brain, liver, or muscle cells, and organize themselves into three-dimensional structures such as tissues and organs.

The fate of each cell — what type of specialized cell it will become — depends on which genes are turned on or off in the cell. These patterns of gene activity shape the cell’s structure and function, enabling it to take on a specific role in the body.

But this decision isn’t up to individual cells. They constantly send and receive chemical signals to and from neighboring cells, which help them understand where they are, what stage of development they are in, and what they should become. These messages spread through multi-step sequences called signaling pathways, which translate external signals into specific changes in gene activity in the cell.

For researchers, being able to retrace the sequence of instructions a cell has received would offer a powerful way to understand how tissues develop and how these processes go awry in disease. 

But this has been difficult to achieve because scientists have long assumed that the effects of signaling pathways vary widely across cell types, meaning they would need to map each pathway separately in each cell type — an arduous and painstaking process.

Now, in a new study led by MIT assistant professor of biology and Whitehead Institute for Biomedical Research member Pulin Li and graduate student Nicholas Hutchins, researchers have discovered that each signaling pathway leaves behind a unique “fingerprint” — a distinctive pattern of gene activity that reflects the particular signals the cell has encountered.

Importantly, these fingerprints are consistent across different cell types for the same signaling pathway, which means that instead of mapping each cell type separately, scientists can reconstruct signaling histories across many cell types using these pathway-specific fingerprints.

This discovery was made possible through a machine learning model called IRIS. This model can detect fingerprints of different signaling pathways and pinpoint which signals a cell received at different stages of development inside an embryo, even for cell types it hasn’t encountered before. 

This artificial intelligence-driven approach marks a major advance over traditional methods, which require researchers to experimentally test every pathway in every possible cell type, and opens up the possibility to comprehensively map the signaling histories of every cell inside a mouse or human embryo at an unprecedented scale.

“Think of voice recognition systems like Siri, which are trained mainly in English, but then use that training to help them recognize other languages,” says Li. “This is called transfer learning, and this is why IRIS can work across many different cell types.”

The researchers’ detailed open-access findings, published in the journal Nature Methods on Sept. 8, could accelerate stem cell engineering for regenerative medicine and improve the creation of organoids — miniature, 3D models that mimic real organs — for studying disease mechanisms and testing new drugs. This is because once researchers learn the pattern of signals that drives a stem cell to become a specific cell type, they can recreate those signals to control the fate of stem cells in a lab or medical setting.

IRIS is a neural network-based model, which, in essence, is an AI-driven system designed to recognize patterns in complex data, similar to how our brains spot patterns. It examines a cell’s overall gene activity and estimates which signaling pathways were likely “on” at specific times during development.

Li and Hutchins trained IRIS on a large experimental dataset that measured how thousands of human embryonic stem cells responded to dozens of combinations of six major signaling pathways at multiple stages of development. This created a comprehensive map, or atlas, of how signaling combinations influence cell behavior. 

The team then tested IRIS using single cells from mouse embryos during gastrulation, a stage when cells are rapidly branching into different fates. IRIS could accurately predict when and where specific signaling pathways would activate in cells destined to become part of heart, gut, muscle, and spinal cord tissue. This variation in signaling molecules is what guides cells to form the right structures in the right places.

With this approach, scientists can not only begin to understand the fundamentals of cell-to-cell communication, but also gain a practical roadmap for guiding stem cells into specific, functional cell types in the lab.

When the researchers employed IRIS to identify signals needed to create a cell type critical for lung development, the model predicted that activating a specific signaling pathway would encourage lung-specific development. Experiments in mouse embryos confirmed the model’s prediction. By identifying the precise combinations of signals that drive lung cell development, they can more reliably generate accurate, lab-grown models of lung tissue.

“In these ways, IRIS is helping us decode the language cells use to talk to each other at a much faster rate than we could realistically achieve through experiments,” Hutchins says.

These improved models would allow researchers to study diseases like asthma, lung cancer, and pulmonary fibrosis, in which lung tissue becomes scarred, often without a known cause. They can then use these models to test potential therapies, and ultimately design regenerative treatments that can repair the damaged tissue.

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Satellite data reveal how Antarctica’s ice cliffs behave over time

With rising temperatures, the buttressing ice shelves at the edges the Antarctic ice sheet are melting and calving off at record rates, leaving behind sheer cliffs of solid ice. The stability of these exposed ice cliffs could influence how Antarctica further breaks apart and contributes to sea level rise around the world. 

Scientists have assumed that an ice cliff’s stability depends on its height: Ice cliffs that are taller than 100 meters — about the height of the Statue of Liberty — should collapse under their own weight. And once a cliff sloughs off, it should expose even taller, inland cliffs that collapse in turn. At least, that’s been the idea.

But researchers at MIT and the Woods Hole Oceanographic Institution (WHOI) have found that the stability of an ice cliff depends on more than its height. And even when a cliff topples, it doesn’t necessarily set off a runaway collapse. 

In a study appearing today in Science, the team presents an analysis of over 15,000 ice cliffs in Antarctica that were monitored by satellites over a four-year period. They observed how the ice cliffs and the larger ice sheet evolved over time, and found that those ice cliffs that collapsed did so at a much faster rate than scientists had predicted. But these collapsing cliffs also quickly stabilized, instead of continuing to erode the larger ice sheet. 

“We found that when the cliffs were retreating, they were doing so faster than what has been modeled, which would mean more ice loss and higher contributions of sea level rise,” says study author Caroline Needell, a graduate student in the MIT-WHOI Joint Program. “But because we found that the retreat was short-lived, and all the glaciers eventually stabilized, that would suggest that things won’t be so bad. We don’t see this runaway effect.”

The study’s co-authors are Catherine Walker, assistant scientist at WHOI, and Jeremy Bassis, associate professor at the University of Michigan.

Ice height

In glacial science, ice cliff collapse is described by a process known as marine ice cliff instability (MICI), which assumes that if an ice cliff exceeds a critical height, it will collapse. If then a taller cliff is exposed, it too should collapse, triggering a cascade of instabilities that shrink and erode the ice sheet over time. 

In previous studies, scientists have characterized MICI mainly by modeling the physical properties of ice, scaling these relationships up to the size of an ice cliff and combining these predictions with a few observations of actual ice cliffs in Antarctica. Through these efforts, scientists had determined that ice cliffs become unstable and collapse when they are taller about 100 meters.  

“Predictive ice-sheet models that have been used so far to represent ice cliff instability just take into account cliff height,” Needell notes. “That’s the only variable that matters. And once the cliff height reaches the critical threshold, usually 100 meters, it should initiate this runaway effect of ice sheet retreat.”

But she and her colleagues wondered: How tall do ice cliffs really get? And when they collapse, do they really set off a runaway retreat? 

To answer these questions, they looked to data collected by NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) — a satellite that passes over the Earth’s polar regions and uses a laser altimeter to measure the height of ice sheets, glaciers, sea ice, and the level of the ocean in and around Antarctica. 

The team collected the satellite’s data from 2019 to 2023, which included measurements every three months of over 15,000 ice cliffs. From this dataset, they observed that the average ice cliff was about 30 meters tall — much shorter than the proposed critical height. But they did see a few rare ice cliffs that exceeded 100 meters. 

They also looked for other features that might influence a cliff’s stability. Interestingly, they found that ice cliffs that more or less stayed in place over time also had thicker mélange — a term for the slushy mix of broken icebergs and sea ice that gathers at the front of an ice cliff. 

“We measured mélange height and found taller cliffs have thicker mélange, which could be a built-in stabilizing effect,” Needell explains.

The satellite data also showed that the height of the surrounding water can stabilize a cliff: The deeper the water, the more it can buoy and push back against the cliff, keeping it from collapsing. 

Glacial speed bump

“After we did that global analysis, we thought, ok, let’s zoom in on the tallest cliffs and see how they’re behaving,” Needell says.

The team focused in on four regions around the Antarctic ice sheet where the satellite captured the tallest ice cliffs, each about 100 meters tall, with one that was 127 meters tall. They compiled measurements of these four cliffs and how they evolved every three months, over four years. 

From these measurements, they saw that indeed, the tallest cliffs collapsed, and the ice sheet in those regions retreated, at a surprisingly faster rate than MICI models had predicted. 

“But that retreat was short-lived,” Needell notes. 

After that, the ice spread back out toward the ocean.

“It’s this rapid retreat, punctuated by periods of stabilization,” Needell says. “That was puzzling to us. Then, we thought: We need to look at all the things that affect cliff height.”

The first thing they considered was the topography of the land underneath the ice. If that topography is relatively flat, then the slope of the overlying ice sheet reflects that actual height of the ice itself. But if there’s a bump or rise in the land, the ice sitting directly over that bump is in fact shorter than it appears. The topography then could act as a literal speed bump, thinning the overlying ice, and making it less likely to collapse. 

When the researchers checked topographic measurements of Antarctic, they found that indeed, ice cliffs stabilized around regions where the land happened to rise up. 

They also found that the taller a cliff is, the faster they “thin out” — as they collapse, once tall cliffs settle into shorter, more stable cliffs that prevents further collapse. 

“Now we know what to look for,” Needell says. “We really need to know the bed topography, and we need to know the ice thinning rate, in order to get ice cliff instability right, because this value really matters in the context of projecting sea level rise.” 

This research was supported, in part, by NASA, the U.S. National Science Foundation, and the DOMINOS project, a component of the International Thwaites Glacier Collaboration.

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